This PDF file contains the front matter associated with SPIE
Proceedings Volume 7292, including the Title Page, Copyright
information, Table of Contents, Introduction, and the
Conference Committee listing

A class of low-cost, wireless sensor has been developed at the University of Texas at Austin to monitor the performance
of reinforced and prestressed concrete members in civil infrastructure systems. The sensors are designed to be
interrogated in a wireless manner as part of a routine inspection. The sensors do not require batteries or connections to
external power supplies. As such, the sensors are intended to be maintenance free over the service life of the
infrastructure system.
Research efforts to date have focused on detecting the onset of corrosion. It is envisioned that the sensors would be
attached to the reinforcement cages before placement of the concrete. The results of long-term exposure tests will be
used in this presentation to demonstrate the potential and reliability of the resonant sensors.

The focus of this paper is on real-time damage detection in reinforcing fiber bundles and composites using high-speed
photography and image analysis. In other words, the end of a reinforcing fiber bundle or composite is imaged and the
sequence of fiber fracture is monitored using a high-speed camera. These studies were undertaken using as-received and
silane-treated custom-made optical fibers of around 12 μm diameter and E-glass fibers of 15 (±3) μm diameter.
The first part of this paper reports on the techniques that were developed to produce void-free test specimens and the
procedures used for imaging the end of the fiber bundle and composite during tensile loading. Evanescent wave
spectroscopy was used to study the effect of silane treatment on the cross-linking kinetics of an epoxy/amine resin
system. Conventional piezo-electric acoustic emission (AE) transducers were used to monitor the acoustic events
occurring during the tensile test. The signals from the AE transducers were used to trigger the high-speed camera.
The second part of this paper presents details of the image analysis routines that were developed to track the light
intensity transmitted through individual fibers during tensile loading. Good correlation was observed between the
transmitted light intensity and the AE signals.

Elevated civil structure systems, such as communication towers and water tanks, are prone to higher mode vibration and
earthquake induced damages. To mitigate damages, however, the structures are retrofitted with conventional (e.g. steel
casing) and/or emerging techniques (e.g. smart structures). Smart structure entails integration of system behavior, control
design and actuators. In this paper, utility of smart structures is illustrated through an elevated water tank concrete
column. The concrete column is modeled as a continuous system, using the Lagrangian formulation, and linear quadratic
regulator (LQR) is used for the control system, and shape memory alloy (SMA) for actuation. The water tank is excited
with the 1940 El-Centro earthquake record. A sensitivity analysis is performed on the controller error and penalizing
constants, as well as actuator location and angle of the connection. The four control variables that can be analyzed for
the controller are: Rr, Qr, Re, and Qe, which are the control penalty, error penalty, measurement noise and process noise,
respectively. The connection height on the beam and angle of the actuator is also analyzed for optimal performance.
From the sensitivity analysis, the most efficient controller configuration is identified for further analysis of the structure.
Optimal actuator configuration can be found based on the reduction of displacement versus the amount of energy used. It
has been shown that using the SMA, the seismic demand on the concrete column is reduced using the SMA.

In this study, taking advantage of carbon nano-fiber paper's (CNP) small and thin size, high conductivity, rapid
increasing temperature in low voltage, higher steady state temperature, electrical and heat, it found out a way that place
argentine glue electrode on the CNP's surface and use a kind of transmitting-heat glue fixed thermal couple for testing
the temperature change of CNP following by different voltage in room temperature and adiabatic circumstance. The
electrode attachment method on the CNP developed. Experimental validation studies have verified that the CNP exhibit
highly electrical and heat property and develop a new self-heating concrete using CNP.

Globally, civil infrastructures are deteriorating at an alarming rate caused by overuse, overloading, aging, damage or
failure due to natural or man-made hazards. With such a vast network of deteriorating infrastructure, there is a
growing interest in continuous monitoring technologies. In order to provide a true distributed sensor and control
system for civil structures, we are developing a Structural Nervous System that mimics key attributes of a human
nervous system. This nervous system is made up of building blocks that are designed based on mechanoreceptors as
a fundamentally new approach for the development of a structural health monitoring and diagnostic system that
utilizes the recently developed piezo-fibers capable of sensing and actuation. In particular, our research has been
focused on producing a sensory nervous system for civil structures by using piezo-fibers as sensory receptors, nerve
fibers, neuronal pools, and spinocervical tract to the nodal and central processing units. This paper presents up to
date results of our research, including the design and analysis of the structural nervous system.

This paper addresses the issue of intermittent data loss during transmission of wireless network sensors and the
application of the reconstruction signal for damage detection with the damage locating vector (DLV) method. The
algorithm makes use of frequencies which contribute significant amount of energy in the signal based on Fourier
transform. As the amplitudes are uncertain due to lost data, the Fourier amplitudes are estimated based on least-square fit
of only the measured portions of the signal. The lost portions are reconstructed through inverse Fourier transform. The
procedure is iterated until the discrepancy between estimated lost portions of two consecutive iterations is below a set
threshold. This threshold and the power spectral threshold to demarcate the significant frequencies are selected based on
results from numerically simulated signals. The reconstructed signals are used with the DLV method for damage
detection to investigate the practicality of this procedure. A cantilever truss structure with a pre-stressed cable was
monitored using six wireless sensors. The pre-stressed cable was cut mid-way during random load application and data
collection. The results obtained support the use of the reconstructed signal within the framework of the DLV method.

Economic and reliable online health monitoring strategies are very essential for safe operation of civil, mechanical and
aerospace structures. Furthermore, a PZT sensor self-diagnostic and validation procedure is quite important issue for
successful impedance-based SHM system's implementation. This study presents online sensor self-diagnosis technique
over structural health monitoring (SHM) strategies using wireless impedance sensor nodes. The wireless impedance
sensor node incorporating a miniaturized impedance measuring chip, a microcontroller, and a radio-frequency (RF)
telemetry is equipped with the capabilities for temperature-sensing, multiplexing of several sensors, and local data
analysis. A temperature effects-free sensor self-diagnosis algorithm is embedded into the sensor node and its feasibility
is examined from the experiments monitoring the integrity of each piezoelectric sensor on a wireless sensor network.

Wireless acquisition and transmission system of the sensing signals of the smart cement-based sensors is designed for
stress/strain monitoring of concrete structures, the conception and the sensing principle of smart cement-based sensors
are introduced, and the design method is presented based on the characters of the signals of smart cement-based sensors
and the modularized program. The operating principle of the wireless acquisition and transmission system is especially
analyzed, and the hardware circuit and the integration method are discussed in detail. The experiment of the designed
wireless acquisition and transmission system is finished, and the experimental results show that the presented wireless
acquisition and transmission system of the sensing signals of smart cement-based sensors has such advantages as simple
circuit, easy to realize, high reliability, low cost, convenient setting and good practicability, and it is suitable for
application in health monitoring of concrete structures.

Lead zirconate titanate (PZT) based impedance transducers have been widely used in structural health monitoring (SHM).
They have shown excellent capabilities in evaluation of structural health in terms of damage, deformation and load
monitoring. However, in applications of large scale structures or in the case that structure to be monitored is difficult to
access, the accuracy of data acquired is compromised due to long cables used to connect sensors and data acquisition
equipment. Wireless technology is therefore desired in controlling health monitoring of aerospace, civil and mechanical
structures to solve the problem. This paper presents a newly developed wireless impedance analyzer which is applied to
monitor structural damage. The reliability of the wireless data acquisition system is analyzed by comparing signatures
acquired using wireless impedance analyzer against those obtained from traditional cable connection.

This paper describes an autonomous wireless system that generates road safety alerts, in the form of SMS and
email messages, and sends them to motorists subscribed to the service. Drivers who regularly traverse a particular
route are the main beneficiaries of the proposed system, which is intended for sparsely populated rural
areas, where information available to drivers about road safety, especially bridge conditions, is very limited. At
the heart of this system is the SmartBrick, a wireless system for remote structural health monitoring that has
been presented in our previous work. Sensors on the SmartBrick network regularly collect data on water level,
temperature, strain, and other parameters important to safety of a bridge. This information is stored on the
device, and reported to a remote server over the GSM cellular infrastructure. The system generates alerts indicating
hazardous road conditions when the data exceeds thresholds that can be remotely changed. The remote
server and any number of designated authorities can be notified by email, FTP, and SMS. Drivers can view road
conditions and subscribe to SMS and/or email alerts through a web page. The subscription-only form of alert
generation has been deliberately selected to mitigate privacy concerns. The proposed system can significantly
increase the safety of travel through rural areas. Real-time availability of information to transportation authorities
and law enforcement officials facilitates early or proactive reaction to road hazards. Direct notification of
drivers further increases the utility of the system in increasing the safety of the traveling public.

Strain analysis due to vibration can provide insight into structural health. An Extrinsic Fabry-Perot Interferometric
(EFPI) sensor under vibrational strain generates a non-linear modulated output. Advanced signal processing techniques,
to extract important information such as absolute strain, are required to demodulate this non-linear output. Past research
has employed Artificial Neural Networks (ANN) and Fast Fourier Transforms (FFT) to demodulate the EFPI sensor for
limited conditions. These demodulation systems could only handle variations in absolute value of strain and frequency of
actuation during a vibration event. This project uses an ANN approach to extend the demodulation system to include the
variation in the damping coefficient of the actuating vibration, in a near real-time vibration scenario. A computer
simulation provides training and testing data for the theoretical output of the EFPI sensor to demonstrate the approaches.
FFT needed to be performed on a window of the EFPI output data. A small window of observation is obtained, while
maintaining low absolute-strain prediction errors, heuristically. Results are obtained and compared from employing
different ANN architectures including multi-layered feedforward ANN trained using Backpropagation Neural Network
(BPNN), and Generalized Regression Neural Networks (GRNN). A two-layered algorithm fusion system is developed
and tested that yields better results.

Image thresholding in the High Resolution Target Movement Monitor (HRTMM) is examined. The HRTMM was
developed at the Missouri University of Science and Technology to detect and measure wall movements in underground
mines to help reduce fatality and injury rates. The system detects the movement of a target with sub-millimeter accuracy
based on the images of one or more laser dots projected on the target and viewed by a high-resolution camera. The
relative position of the centroid of the laser dot (determined by software using thresholding concepts) in the images is the
key factor in detecting the target movement. Prior versions of the HRTMM set the image threshold based on a manual,
visual examination of the images. This work systematically examines the effect of varying threshold on the calculated
centroid position and describes an algorithm for determining a threshold setting. First, the thresholding effects on the
centroid position are determined for a stationary target. Plots of the centroid positions as a function of varying
thresholds are obtained to identify clusters of thresholds for which the centroid position does not change for stationary
targets. Second, the target is moved away from the camera in sub-millimeter increments and several images are obtained
at each position and analyzed as a function of centroid position, target movement and varying threshold values. With
this approach, the HRTMM can accommodate images in batch mode without the need for manual intervention. The
capability for the HRTMM to provide automated, continuous monitoring of wall movement is enhanced.

Recently, system augmentation has been combined with nonlinear feedback auxiliary signals to provide sensitivity
enhancement in both linear and nonlinear systems. Augmented systems are higher dimensional linear systems
that follow trajectories of a nonlinear system one at a time. These augmented systems are subject to a specialized
augmented forcing which enforces the augmented system will exactly reproduce the trajectory of the nonlinear
system when projected onto the lower dimensional (physical) system. Augmented systems have additional
benefits outside of handling nonlinear systems, which makes them more desirable than regular linear systems
for sensitivity enhancing control. One of the key advantages of augmented systems is the complete control over
the augmented degrees of freedom, and the additional sensor knowledge from the augmented variables. These
sensing and actuation features are very useful when only few physical actuators and sensors can be placed.
Such restrictions severely limit the usefulness of traditional linear sensitivity enhancing feedback approaches.
Another benefit of the augmentation is that the control exerted on the augmented degrees of freedom does not
require any physical energy, rather it is just signal processing. In this work, the benefits of system augmentation
are explored by using few actuators and sensors. In addition to increased sensitivity for both global and local
parameter changes, a study of increasing the sensitivity of local changes, while decreasing the sensitivity of global
changes is conducted. Numerical simulations for a linear cantilevered beam with a single piezo-actuator and two
sensors are used to validate the approach and discuss the effects of noise.

Matching pursuit (MP) is an adaptive signal decomposition technique and can be applied to process
Lamb waves, such as denoising, wave parameter estimation, and feature extraction, for health
monitoring applications. This paper explored matching pursuit decomposition using Gaussian and
chirplet dictionaries to decompose/approximate Lamb waves and extract wave parameters. While
Gaussian dictionary based MP is optimal for decomposing symmetric signals, chirplet dictionary
based MP is able to decompose asymmetric signals, e.g., dispersed Lamb wave. The extracted
parameter, chirp rate, from the chirplet MP can be used to correlate with two Lamb wave modes, S0
and A0.

Image segmentation for quantifying damage based on Bayesian updating scheme is proposed for diagnosis and prognosis
in structural health monitoring. This scheme enables taking into account the prior information of the state of the
structures, such as spatial constraints and image smoothness. Bayes' law is employed to update the segmentation with
the spatial constraint described as Markov Random Field and the current observed image acting as a likelihood function.
Segmentation results demonstrate that the proposed algorithm holds promise of searching a crack area in the SHM image
and focusing on the real damage area by eliminating the pseudo-shadow area. Thus more precise crack estimation can be
obtained than the conventional K-means segmentation by shrinking the fuzzy tails which often exist on both sides of the
crack tips.

This paper presents a structural health monitoring system for judging structural condition of metallic plates by analyzing
ultrasonic waves. Many critical accidents of structures like buildings and aircrafts are caused by small structural errors;
cracks and loosened bolts etc. This is a reason why we need to detect little errors at an early stage. Moreover, to improve
precision and to reduce cost for damage detection, it is necessary to build and update the database corresponding to
environmental change. This study focuses our attention on the automatable structures, specifically, applying artificial
immune system (AIS) algorithm to determine the structure safe or not. The AIS is a novelty computational detection
algorithm inspired from biological defense system, which discriminates between self and non-self to reject nonself cells.
Here, self is defined to be normal data patterns and non-self is abnormal data patterns. Furthermore, it is not only pattern
recognition but also it has a storage function. In this study, a number of impact resistance experiments of duralumin
plates, with normal structural condition and abnormal structural condition, are examined and ultrasonic waves are
acquired by AE sensors on the surface of the aluminum plates. By accumulating several feature vectors of ultrasonic
waves, a judging method, which can determine an abnormal wave as nonself, inspired from immune system is created.
The results of the experiments show good performance of this method.

The use of coupled Rayleigh-like waves in aluminum plates has been investigated with a view towards applications for
the non-destructive inspection of aircraft structures. Such waves can be generated using standard Rayleigh wave
transducers at frequencies, so that the Rayleigh wavelength corresponds to approximately half the plate thickness. The
Rayleigh-like wave, which can be interpreted as the superposition of the fundamental Lamb modes, transfers energy
between both surfaces with a characteristic distance called the beatlength. Experimentally the reflected wave can be
measured using either standard pulse-echo equipment or a laser vibrometer. The energy transfer between the plate
surfaces results in a good sensitivity for the detection of small defects on both surfaces. Using a combination of
evaluation in the time and frequency domain, the defect location and damaged plate side can be accurately determined.
Due to the beating phenomenon, the Rayleigh-like wave can propagate past regions with surface defects or features. This
allows for the remote detection of defects in areas where access is restricted by structural features, such as stiffeners and
stringers. This has been shown experimentally and verified from Finite Difference simulations.

Guided waves generated and measured using surface-bonded Lead Zirconate Titanate (PZT) transducers have been
widely used for structural health monitoring (SHM) and nondestructive testing (NDT) applications. For selective
actuation and sensing of Lamb wave modes, the sizes of the transducers and the driving frequency of the input waveform
should be tuned. For this purpose, a theoretical Lamb wave tuning curve (LWTC) of a specific transducer size is
generally obtained. Here, the LWTC plots each Lamb wave mode' amplitude as a function of the driving frequency.
However, a discrepancy between experimental and existing theoretical LWTCs has been observed due to little
consideration of the bonding layer and the energy distribution between Lamb wave modes. In this study, calibration
techniques for the theoretical LWTCs are proposed. First, a theoretical LWTC is developed when circular shape of PZTs
is used for both Lamb wave excitation and sensing. Then, the LWTC is calibrated by estimating the effective PZT size
with PZT admittance measurement. Finally, the energy distributions among symmetric and antisymmetric modes are
taken into account for better prediction of the relative amplitudes between Lamb wave modes. The effectiveness of the
proposed calibration techniques is examined through numerical simulations and experimental estimation of the LWTC
using the circular PZT transducers instrumented on an aluminum plate.

This paper presents spectral element formulation which simulates high frequency dynamic responses generated by PZT
transducers bonded on a thin plate. A two layer beam model under 2-D plane strain condition is developed to represent
fundamental Lamb wave modes induced by a piezoelectric (PZT) layer rigidly bonded on a base plate. Mindlin-
Herrmann and Timoshenko beam theories are employed to represent the first symmetric and anti-symmetric Lamb wave
modes on a base plate, respectively. The Euler-Bernoulli beam theory and 1-D linear piezoelectricity are used to model
the electro-mechanical behavior of a PZT layer. The equations of motions of a two layer beam model are derived through
Hamilton's principle. The necessary boundary conditions associated with the electro-mechanical properties of a PZT
layer are formulated in the context of dual functions of a PZT layer as an actuator and a sensor. General spectral shape
functions of response field and the associated boundary conditions are obtained through equations of motion transformed
into frequency domain. Detailed spectral element formulation for composing the dynamic stiffness matrix of a two layer
beam model is presented as well. The validity of the proposed spectral element is demonstrated through a numerical
example.

Propagation of torsional elastic waves in the clad core is addressed in this paper. The shear velocity of the core is slightly
smaller than that in the cladding. Core with cladding of different finite thickness and infinite thickness is investigated.
Two types of modes, guided and leaky modes are examined with the discussion of motion in waveguide. Phase, group,
and energy velocities, cutoff frequencies are analyzed and the results of first three modes are presented. The change of
dispersion curves due to variation of thickness of cladding is discussed and it is found that when the thickness increases
the results of finite clad core will approach those of infinite clad core in guided mode, but not in leaky mode. Below
cutoff frequencies the wavenumber becomes complex in infinite clad core, while it is pure imaginary in finite clad cores.
The group and energy velocity are presented and in leaky mode the group velocity becomes abnormal, while the energy
velocity is physically meaningful.

This paper reports a fundamental study of the coupling between highly nonlinear waves, generated in a one
dimensional granular chain of particles, with linear elastic media, for the development of a new Non Destructive
Evaluation and Structural Health Monitoring (NDE/SHM) paradigm. We design and use novel acoustic actuators
to excite compact highly nonlinear solitary waves in a one-dimensional linear elastic rod and investigate the pulse
propagation across the interface. To model the actuator and rod system we use Finite Element Analysis (Abaqus)
and obtain excellent agreement between the experimental observations and the numerical results. We also study
the response of the system to the presence of defects (cracks) in the steel rod, by comparing the wave propagation
properties in pristine and cracked test objects. The obtained results encourage the use of highly nonlinear waves
as an effective tool for developing a new, viable NDE/SHM method.

In this paper, we present our progress on developing Sonic Infrared (IR) Imaging for structural health monitoring on
steel structures. Sonic IR imaging is a fast, wide-area novel imaging NDE/SHM technique. Ultrasonic excitation was
used to stimulate heating in defects, combining with Infrared Imaging to identify defects in structures. The whole
process takes only about a second. We have been working on some steel specimens used in some typical steel
structures. Actual heating patterns are extracted from the IR images and the actual temperature changes are mapped out.
Theoretical computing is also carried out to calculate the heating pattern in the specimens with the experimental results
as benchmarks.

We present several findings related to acoustic emission detection using a MEMS sensor. The MEMS sensor is a
capacitive resonant transducer, fabricated in the PolyMUMPs process, with a resonant frequency near 160 kHz. In this
paper, the design, initial characterization, amplification electronics, and packaging of the sensor system are reviewed.
We present results from an experiment that compares the MEMS sensor system to a commercial PZT sensor by
comparing the response of each sensor to a pencil lead break on a plate. In addition, we describe the noise
characterization of the MEMS sensor system, comparing the predicted noise voltage to the measured value. This
analysis reveals that the electronic noise from the amplifier is significantly greater than the noise from the sensor,
suggesting that an amplifier with less noise would increase the sensitivity of the MEMS sensor system. We describe the
design of a new, transimpedance amplifier and its noise characterization, showing the new amplifier design has less
noise than the old design. The experiment comparing the commercial PZT sensor and the MEMS sensor system is
repeated using the new amplifier, and we present results showing an increase in sensitivity of the MEMS sensor system.
Finally, we present results from an experiment comparing the ability of the commercial PZT sensor and the MEMS
sensor system with the new amplifier to detect pencil lead breaks performed a large distance from each sensor.

Experimental studies were performed using high-fidelity broadband Glaser-NIST conical transducers to
quantify stress waves produced by the elastic collision of a tiny ball and a massive plate. These sensors are sensitive to
surface-normal displacements down to picometers in amplitude, in a frequency range of 20 kHz to over 1 MHz. Both the
collision and the resulting transient elastic waves are modeled with the finite element program ABAQUS and described
theoretically through a marriage of the Hertz theory of contact and a full elastodynamic Green's function found using
generalized ray theory. The calculated displacements were compared to those measured through the Glaser-NIST sensors.

The installation of a structural monitoring system on a medium- to large-span bridge can be a challenging undertaking
due to high system costs and time consuming installations. However, these historical challenges can be eliminated by
using wireless sensors as the primary building block of a structural monitoring system. Wireless sensors are low-cost
data acquisition nodes that utilize wireless communication to transfer data from the sensor to the data repository.
Another advantageous characteristic of wireless sensors is their ability to be easily removed and reinstalled in another
sensor location on the same structure; this installation modularity is highlighted in this study. Wireless sensor nodes
designed for structural monitoring applications are installed on the 180 m long Yeondae Bridge (Korea) to measure the
dynamic response of the bridge to controlled truck loading. To attain a high nodal density with a small number (20) of
wireless sensors, the wireless sensor network is installed three times with each installation concentrating sensors in one
portion of the bridge. Using forced and free vibration response data from the three installations, the modal properties of
the bridge are accurately identified. Intentional nodal overlapping of the three different sensor installations allows mode
shapes from each installation to be stitched together into global mode shapes. Specifically, modal properties of the
Yeondae Bridge are derived off-line using frequency domain decomposition (FDD) modal analysis methods.

This paper describes the design and testing of a wireless sensor network based on the SmartBrick, a low-power
SHM device developed by the authors. The SmartBrick serves as the base station for the network, which utilizes
additional sensor nodes to periodically evaluate the condition of the structure. Each node measures vibration,
tilt, humidity, and strain, and is designed for easy interfacing of virtually any other analog or digital sensor. The
sensor nodes use Zigbee to transmit their data to the base station, which in turn uses the GSM cellular phone
network to provide long-range communication and support for remote control.
The system has been designed from the outset to minimize power consumption, and is projected to operate
autonomously for up to four years without any on-site maintenance, due largely to the minimal power consumption
and rugged design. Remote calibration over the GSM network further increases the autonomy of the system.
Most importantly, it can perform all requisite actions with no cables for power or communication. The focus of
this paper is the addition of short-range wireless communication over Zigbee. This allows a network of several
devices to be used to monitor larger structures, such as multi-span bridges. Results of laboratory testing are
included and discussed in detail, demonstrating the unique capabilities of the proposed SHM system.

Understanding the dynamic behavior of civil engineering structures is important to adequately resolve problems related
to structural vibration. The dynamic properties of a structure are commonly obtained by conducting a modal survey that
can be used for model updating, design verification, and improvement of serviceability. However, particularly for largescale
civil structures, modal surveys using traditional wired sensor systems can be quite challenging to carry out due to
difficulties in cabling, high equipment cost, and long setup time. Smart sensor networks (SSN) offer a unique
opportunity to overcome such difficulties. Recent advances in sensor technology have realized low-cost smart sensors
with on-board computation and wireless communication capabilities, making deployment of a dense array of sensors on
large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized
data acquisition and processing are a common practice, the SSN requires decentralized algorithms due to the limitation
associated with wireless communication; to date such algorithms are limited. This paper proposes a new decentralized
hierarchical approach for modal analysis that reliably determines the global modal properties and can be implemented on
a network of smart sensors. The efficacy of the proposed approach is demonstrated through several numerical examples.

Acceleration and impedance signatures extracted from a structure are appealing features for a prompt diagnosis on
structural condition since those are relatively simple to measure and utilize. However, the feasibility of using them for
damage monitoring is limited when their changes go undisclosed due to uncertain temperature conditions, particularly
for large structures. In this study, temperature effect on hybrid damage monitoring of prestress concrete (PSC) girder
bridges is presented. In order to achieve the objective, the following approaches are implemented. Firstly, a hybrid
monitoring algorithm using acceleration and impedance signatures is proposed. The hybrid monitoring algorithm mainly
consists of three sequential phases: 1) the global occurrence of damage is alarmed by monitoring changes in acceleration
features, 2) the type of damage is identified as either prestress-loss or flexural stiffness-loss by identifying patterns of
impedance features, 3) the location and the extent of damage are estimated from damage index method using natural
frequency and mode shape changes. Secondly, changes in acceleration and impedance signatures were investigated under
various temperature conditions on a laboratory-scaled PSC girder model. Then the relationship between temperatures
and those signatures is analyzed to estimate and a set of empirical correlations that will be utilized for the damage
alarming and classification of PSC girder bridges. Finally, the feasibility of the proposed algorithm is evaluated by using
a lab-scaled PSC girder bridge for which acceleration and impedance signatures were measured for several damage
scenarios under uncertain temperature conditions.

A glulam beam retired from the field and without visible indications of wood decay was used. Towards detection and
assessing wood decay, X-ray computer tomography and ultrasonic measurements were carried out. It was observed that
decrease in mass density with increasing levels of wood decay affects x-rays attenuation and allows radioscopy to detect
and assess wood decay. To detect and assess decay when only one lateral side of the beam is available, a modified
impulse-echo was developed. The modified impulse-echo approach is based on observing the dynamic response of the
glulam beams to the drop of a steel sphere onto a steel plate coupled to the glulam beam lamina. It was observed that
monitoring certain frequency bands allows detection and assessment of wood decay. The selection of these frequency
bands requires knowledge of the nominal beam transverse dimensions. Because of the high ultrasonic material
attenuation values of decayed wood as compared with those of sound wood, the area under the power spectral density in
these frequency bands is smaller in regions of decayed wood. Results show that results from both X-ray computer
tomography and impulse-echo measurements are consistent with each other and can be used to detect and assess wood
decay in structural lumber.

An acoustic emission (AE) approach to evaluate low temperature cracking susceptibility of asphalt binders is presented.
Thin films of asphalt binders were bonded to granite substrates and exposed to temperatures ranging from 15°C to -
50°C. Differential thermal contraction between granite substrates and asphalt binders induces progressively higher
thermal stress in the binders resulting in thermal crack formation, which is accompanied by a release of elastic energy in
the form of transient waves. Using piezoelectric sensors (Digital Wave, Model B-1025), a four-channel acoustic
emission system was used to record the acoustic emission activity during the binder/granite cooling process. Assuming
the cracking temperature (Tcr) to be the temperature at which the AE signal energy exceeds a pre-selected threshold
energy level, this AE testing approach was found to be sensitive and repeatable for predicting cracking temperatures
(Tcr) in four SUPERPAVE core asphalt binders. These AE-based Tcr predictions showed strong correlation (R2 = 0.9)
with predictions based on either AASHTO TP1 or MP1A protocols. Unlike TP1 and MP1A protocols, the presented AE
approach does not require the use of sophisticated software for predicting thermal stresses, and no assumption is required
regarding the testing cooling rate and the binder coefficient of thermal contraction.

We propose a novel approach for optimal actuator and sensor placement for active sensing-based structural health
monitoring (SHM). Of particular interest is the optimization of actuator-sensor arrays making use of ultrasonic wave
propagation for detecting damage in thin plate-like structures. Using a detection theory framework, we establish the
optimum configuration as the one which minimizes Bayes risk. The detector incorporates a statistical model of the
active sensing process which accounts for both reflection and attenuation features, implements pulse-echo and pitchcatch
actuation schemes, and takes into account line-of-site. The optimization space was searched using a genetic
algorithm with a time varying mutation rate. For verification, we densely instrumented a concave-shaped plate and
applied artificial, reversible damage to a large number of randomly generated locations, acquiring active sensing data for
each location. We then used the algorithm to predict optimal subsets of the dense array. The predicted optimal
arrangements proved to be among the top performers when compared to large sets of randomly generated arrangements.

A steel box beam in a monorail application is constructed with an epoxy grout wearing surface, precluding visual
inspection of its top flange. This paper describes a sequence of experimental research tasks to develop an ultrasonic
system to detect flaws (such as fatigue cracks) in that flange, and the results of a field test to demonstrate system
performance. The problem is constrained by the fact that the flange is exposed only along its longitudinal edges, and by
the fact that permanent installation of transducers at close spacing was deemed to be impractical. The system chosen for
development, after experimental comparison of alternate technologies, features angle-beam ultrasonic transducers with
fluid coupling to the flange edge; the emitting transducers create transverse waves that travel diagonally across the width
of the flange, where an array of receiving transducers detect flaw reflections and flaw shadows. The system rolls along
the box beam, surveying (screening) the top flange for the presence of flaws.
In a first research task, conducted on a full-size beam specimen, we compared waves generated from different transducer
locations, either the flange edge or the web face, and at different frequency ranges. At relatively low frequencies, such
as 100 kHz, we observed Lamb wave modes, and at higher frequency, in the MHz range, we observed nearlylongitudinal
waves with trailing pulses. In all cases we observed little attenuation by the wearing surface and little
influence of reflection at the web-flange joints. At the conclusion of this task we made the design decision to use edgemounted
transducers at relatively high frequency, with correspondingly short wavelength, for best scattering from flaws.
In a second research task we conducted experiments at 55% scale on a steel plate, with machined flaws of different size,
and detected flaws of target size for the intended application. We then compared the performance of bonded transducers,
fluid-coupled transducers, and angle-beam (wedge) transducers; from that comparison we made the design decision to
use wedges, which beam the wave to increase the scattering from flaws. We also compared the performance of wired
transducers using fluid coupling to that of wireless (inductively coupled) transducers mounted permanently. Although
the wireless transducers achieved flaw detection, the necessary spacing (determined experimentally) would have
required an impractical number of transducers. Therefore, we made the design decision to use wedge transducers with
fluid coupling.
In a third research task we developed and tested a rolling system with a water channel for acoustic coupling, including a
study of its sensitivity to misalignment, and in a fourth task we devised a data display to create a pattern of reflections or
shadows that could be easily interpreted as evidence of a flaw. Finally, we conducted a field test on the full-size system
in a region containing bolt holes, which act as a physical simulation of a flaw, and show successful detection of
reflections and shadows from those holes.

Critical buildings such as hospitals and police stations must remain functional immediately following a major
earthquake event. Due to earthquake effects, they often experience large strains, leading to progressive collapses.
Therefore, monitoring and assessing the large strain condition of critical buildings is of paramount importance to
post-earthquake responses and evacuations in earthquake-prone regions. In this study, a novel large strain sensor
based on the long period fiber grating (LPFG) technology is proposed and developed. CO2 laser induced LPFG
sensors are characterized for such mechanical properties as strain sensitivity in extension and flexure, sensor
stability, and measurement range. For practical applications, the need for LPFG sensor packaging is identified and
verified in laboratory implementations. By introducing various strain transfer mechanisms, the strain sensitivity of
LPFG sensors can be customized for different applications at corresponding strain transfer ratios.

Significant progress has been made in recent years on the design and deployment of optical fibre-based sensors to
monitor the cross-linking (cure) reactions in thermosetting resins. In the current study, the following sensor designs
were used to study cross-linking reactions of an epoxy/amine resin system: (i) intensity-based Fresnel sensors, (ii)
extrinsic fibre Fabry-Perot interferometic (EFPI) sensors, (iii) fibre Bragg grating (FBG) sensors and (iv) sensor designs
to enable transmission, reflection and evanescent wave spectroscopy.
This paper presents a detailed study on a comparison of the above-mentioned techniques for a commercially available
epoxy/amine resin system. Conventional Fourier transform infrared spectroscopy was used as the reference method for
obtaining quantitative data on the cross-linking kinetics. The shrinkage of the resin during cross-linking was monitored
using EFPI and FBG sensors. This paper also discusses the cross-linking data obtained using optical fibre-based
evanescent wave spectroscopy.

Sensing techniques based on Optical Fiber Bragg Grating (FBG) has been increasingly applied in civil engineering
structures. However, it is still lacking of a reliable FBG based accelerometer for structural vibration measurement. In this
study, a novel FBG accelerometer was developed. The developed sensor has high sensitivity for acceleration
measurement especially in low frequency range where the natural modes of civil engineering structures are usually
concerned. Furthermore, the temperature influence can be self-compensated. This paper described the principle of the
sensor and the parameter optimization for improving the sensor's sensitivity in its measurement ranges of magnitude and
frequency. A prototype sensor was manufactured; the optimal viscosity of the damping liquid filled in the sensor was
selected experimentally. The amplitude-frequency relationship, the sensitivity and the linearity of the sensor were gained
through calibration tests. The results of the tests showed that the feasibility of the FBG accelerometer developed are
satisfactory for low frequency vibration measurement.

This paper introduces the concept and development of a strain sensing system for structural application based on the
properties of photonic crystals. Photonic crystals are artificially created periodic structures, usually produced in the thinfilm
form, where optical properties are tailored by a periodicity in the refractive index. The idea of using the crystal as a
sensor is based on the observation that a distortion in the crystal structure produces a change in the reflected bandwidth.
When a photonic crystal is designed to operate in the visible part of the spectrum, a permanent distortion of the film
results in a change in its apparent color. This property makes photonic crystals suitable for permanent monitoring of
structural elements, as any critical changes in the strain field can be promptly and easily detected by visual inspection. A
simple and low-cost example of photonic crystals consists of opals synthesized by vertical deposition. In this
contribution we introduce a target application for the fatigue monitoring of wind turbines, and then provide the reader
with some basic information concerning modeling of the crystal architecture and fabrication of these structures. Next we
discuss their application to strain measurement, specifying how reflection and transmission properties of the opals have
to be designed to satisfy the expected strain response of the sensor. Finally, we present the preliminary results of a
laboratory validation carried out on thin films applied to a rubber support.

A nanostructured sensor based on double wall carbon nanotubes (DWNTs) was fabricated and assessed for hydrogen gas
detection. DWNT networks were used as an active substrate material evaporated with layers of palladium nanoparticles
of three thicknesses 1, 3 and 6 nm. The electrical resistance change of nanosensor with hydrogen gas exposure in
compressed air at room temperature was monitored. The nanostructures were characterized using high resolution
transmission electron microscopy (HRTEM) and atomic force microscopy (AFM). Hydrogen concentrations as low as
0.05 vol% (500 ppm) can be detected at room temperature. Sensitivity values as high as 65% and response times of
about 3 seconds were obtained. The results indicate that DWNT- based sensors exhibit comparable performance as that
for SWNT-based high performance hydrogen sensors, but with potential improvement in mechanical and thermal
resistance associated with the double layer structure.

Anodized aluminum oxide (AAO) membranes are fabricated under different anodization potentials in dilute sulfuric
acid. Here we report the growth of AAO under 10, 15, 20, and 25V. These AAO membranes consist of nanopores with
pore-to-pore distance from 35 to 69 nm. When AAO membranes are kept thin (less than ~500 nm), together with the
unreacted aluminum substrate, interference colors are observed. The inference color of the membrane is changed by its
thickness and the pore-to-pore distance, which is controlled by the anodization time and voltage, respectively. By using
thin film interference model to analyze the UV-Vis reflectance spectra, we can extract the thickness of the membrane.
Thus the linear growth of AAO membrane in sulfuric acid with time during the first 15 minutes is validated. Coating
poly (styrene sulfonate) (PSS) sodium salt and poly (allylamine hydrochloride) (PAH) layer by layer over the surface of
AAO membrane consistently shifts the interference colors. The red shift of the UV-Vis reflectance spectrum is correlated
to the number of layers. This color change due to molecular attachment and increasing thickness is a promising method
for chemical sensing.

This paper describes the application of a novel actuator/sensor technology for the generation and detection of stress
waves in structural materials like concrete. The technology is aimed at developing an innovative NDE scheme based on
the generation of highly nonlinear solitary waves (HNSWs). HNSWs are stress waves that can form and travel in highly
nonlinear systems (i.e. granular, layered, fibrous or porous materials) with a finite spatial dimension independent on the
wave amplitude. Compared to conventional linear waves, the generation of HNSWs does not rely on the use of
electronic equipment (such as an arbitrary function generator) and on the response of piezoelectric crystals or other
transduction mechanism. The results of using these new actuator/sensors to test concrete slabs are presented and
discussed.

This paper presents a biologically inspired sensor network framework for autonomous structural health monitoring
(SHM). The presented sensor network framework transforms desirable characteristics and effective defense mechanisms
of the natural immune system to wireless sensor networks for SHM. The autonomous structural health monitoring is
achieved through an integrated sensor network framework consisting of high computational power sensors, a mobileagent-
based sensor network middleware, and artificial immune pattern recognition (AIPR) methodology for structure
damage detection and classification. An AIPR-based structure damage classifier (AIPR-SDC) has been developed,
which incorporates several novel characteristics of the natural immune system. The performance of the AIPR-SDC has
been validated using a benchmark structure proposed by the IASC-ASCE (International Association for Structural
Control - American Society of Civil Engineers) SHM Task Group. The validation results show a better classification
success rate comparing to some of other classification algorithms. The further study of unsupervised structure damage
classification is also conducted by integrating data clustering techniques and the AIPR method.

Damage detection in engine bladed disks is an extremely important task. While current ultrasonic and eddy current
damage detection techniques are reliable, they are also expensive in cost and cannot be used for in-situ monitoring.
Although global vibration-based damage detection techniques can overcome these challenges, they may not be accurate
due to its low sensitivity to damage. On the other hand, for a periodic structure such as the bladed disk, due to its unique
dynamic characteristics, there is great potential in utilizing a vibration-response-based concept to effectively and
accurately detect damage. The goal of this research is to advance the state-of-the-art of damage detection of bladed disks
by exploring a piezoelectric circuitry network design methodology to enhance the structural vibration damage sensitivity,
particularly through the introduction of intentional circuitry mistuning. Additionally, this research aims to investigate
intentional circuitry mistuning as an alternative to intentional blade mistuning for forced response localization reduction
so that a single design configuration can be adapted to both applications. The effectiveness of the network on inherently
mistuned bladed disks is explored using Monte Carlo simulations, where promising results are illustrated.

The impedance-based damage detection has been recognized to be sensitive to small-sized damage due to its highfrequency
measurement capability. Low-cost impedance measurement circuit has been explored to extract the
piezoelectric impedance/admittance curves by using a resistor that is serially connected with the piezoelectric transducer,
which enables a self-contained sensor unit. In this research, an innovative impedance-based damage detection scheme
is proposed, which combines the key features of the low-cost impedance measurement circuit with those of the
piezoelectric circuitry dynamics. In the new scheme, the piezoelectric transducer is integrated with an inductive circuit.
The resonant effect of the inductive circuitry can greatly increase the measurement amplitude. Moreover, when the
inductance is properly tuned, very significant dynamic interaction between the mechanical structure being monitored
and the electrical circuitry will occur. This results in an order-of-magnitude amplification of the admittance change
upon the occurrence of damage, which can yield much increased damage detection sensitivity. Extensive numerical and
experimental investigations are carried out to demonstrate the new sensing system development.

In this paper, we present a wireless sensing prototype for condition monitoring using acoustic emission signals. It
consists of a 4-member microphone array, a 4-channel 16-bit analog-to-digital converter (ADC) and a wireless node.
The prototype will serve as a platform for sensor and algorithm developments for gearbox condition monitoring. In the
TinyOS operation system, software interfaces are written in the nesC language to link the hardware with high-level
programs. The prototype will eventually collect acoustic emission signals from the microphone array, convert them into
digital data using the ADC, perform local signal processing and transmit the results to another wireless node or a base
station. Two TinyOS programs are also written to test the functionality of the ADC and the wireless nodes. The
programs also demonstrate that data collection and transmission for the one-channel case has been accomplished, though
the four-channel case is still under development. Preliminary results and analysis are presented in the paper. Future
improvements would involve microphone array filtering/denoising, four-channel data transfer, signal processing and
decision making algorithms, and a high-level wireless transmission protocol.

This paper presents the numerical simulation and experimental verification of a semi-active cable vibration control
system. The finite-element analysis "ABAQUS" is used to design and simulate the dynamic characteristics of a cable
structure. The system matrixes 'M', 'C' and 'K' of the simplified cable model is then generated from the finite element
model. A 3 kN MR damper, made by Lord co., is connected to the cable to reduce the vibration. Through a systematic
performance test and system identification procedure, the modified Bou-Wen model is generated to represent the
nonlinear behavior of the MR damper. According to the simplified cable model and MR damper model, the LQG with
continuously-optimal control is used to design the semi-active control system. The scaled-down cable structure is design
and builds according to the finite-element model in ABAQUS. Suitable mass and cable force are added to make the cable
vibration more realistic. A small shaker is designed and mounted onto the cable to generate the excitations with different
amplitudes and frequencies. Both passive and semi-active control cases have been tested. Through the numerical
simulation and experimental test results, the semi-active cable vibration control system with MR damper can reduce the
cable vibration well under different kinds of excitations. This investigation demonstrates the feasibility and capabilities
of a cable vibration control system with MR damper.

Modeling and re-analysis techniques are proposed for predicting the dynamic response of complex structures that
have suffered damage in one or more of their components. When such damages are present, the model of the
healthy structure may no longer capture the system-level response or the loading from the rest of the structure
on the damaged components. Hence, novel models that allow for an accurate re-analysis of the response of
damaged structures are needed in important applications, including damage detection. Herein, such models are
obtained by using a reduced order modeling approach based on component mode synthesis. Because the resonant
response of a complex structure is often sensitive to component uncertainties (in geometric parameters such as
thickness, material properties such as Young's modulus, etc.), novel parametric reduced order models (PROMs)
are developed. In previous work, PROMs have been applied for handling uncertainties in a single substructure.
Herein, PROMs are extended to the general case of multiple substructures with uncertain parameters or damage.
Two damage cases are considered: severe structural deformation (dents), and cracks. For the first damage case,
an approximate method based on static mode compensation (SMC) is used to perform fast re-analysis of the
vibration response of the damaged structure. The re-analysis is performed through a range of locations and
severity levels of the damage. For selected damage locations and levels, the SMC approximation is compared
to full finite element analysis to demonstrate the accuracy and computational time savings for the new method.
For the second damage case (cracks), the vibration problem becomes nonlinear due to the intermittent contact
of the crack faces. Therefore, to estimate the resonant frequencies for a cracked structure, the bi-linear frequency
approximation (BFA) is used for cracks of various lengths. Since BFA is based on linear analyses, it is fast
and particularly well suited for implementation with PROMs for structural re-analysis. In contrast, most other
nonlinear techniques for predicting the dynamic response are computationally intensive and cumbersome. For
validating the proposed PROMs, resonant frequencies predicted using BFA and PROMs are shown to agree very
well with results obtained using a much more expensive commercial finite element tool.

In light of the efforts to improve the performance of micromachined gyroscopes, this paper presents an investigation of
energy loss mechanisms in a SOI-based tuning-fork gyroscope, since these loss mechanisms dictate the value of the
mechanical Quality factor (Q) that has been identified as a critical determinant for achieving high-precision
performance. The numerical models of thermoelastic damping (TED) and anchor loss in the tuning-fork gyroscope
design are created in a FEM software, ANSYS/Multiphysics, according to a thermal-energy method and a separationand-
transfer method, respectively. The calculated results indicate that thermoelastic damping is the dominant loss while
anchor loss is negligible for the gyroscope design. In order to validate the created models, an experimental study on the
Q of the SOI-based tuning-fork gyroscope is consequently conducted. Comparison between the calculated results and the
measured data not only validates the numerical models, but also demonstrates the significant effect of fabrication process
on the final achievable Q values of the fabricated gyroscopes.

Smart materials when interact with engineering structures, should have the capability to sense, measure,
process, and detect any change in the selected variables (stress, damage) at critical locations. These smart materials
can be classified into active and passive depending on the type of the structure, variables to be monitored, and
interaction mechanism due to surface bonding or embedment. Some of the prominent smart materials are
piezoelectric materials, micro fiber composite, polymers, shape memory alloys, electrostrictive and magnetostrictive
materials, electrorheological and magnetorheological fluids and fiber optics. In addition, host structures do have the
properties to support or repel the usage of smart materials inside or on it. This paper presents some of the most
widely used smart materials and their interaction mechanism for structural health monitoring of engineering
structures.

In this paper, a variable camber wing, which comprises a flexible skin, a metal sheet, and a honeycomb structure, is
presented. Shape memory polymer (SMP) is selected for the use of flexible skins. Embedded heating wire springs act as
the activation system for the SMP. Experimental result shows that the inherent separation does not occur between the
heating elements and SMP upon elongation because of elasticity of wire springs. The deformation of SMP skins at
different temperature conditions is analyzed in order to establish the relationship between the deformation of the skin and
pre-strain applied in the SMP skin. Fibre Bragg Grating (FBG) sensors, with flexibility and small size, are bonded on the
surface of the metal sheet to measure the deflection on the some certain points. The relation of the strain on the upper
surface of metal sheet and the deflection of the trailing-edge is established to ensure the position of the bonded FBG
sensors. The curve shape of the bending metal sheet can be reconstructed using the calibration information.

A key objective of the NASA exploration missions is to explore the Solar System and beyond in an
implementation that is safe, sustainable and affordable. One of the major enabling technologies for meeting this
objective is the development of effective autonomous sampling systems for robotic in-situ analysis and scientific
experiments for life and water detection as well as the potential to conduct materials characterization and
mineralogy. Rapid sampling techniques with minimum deterioration of the sample and the potential to capture
volatiles have long been an objective of the planetary science community. Tethered penetrator sampling whether the
penetrator is driven by gravity [Jones et al. 2006], chemical means [Jones et al. 2006], mechanical springs [Backes
et al. 2008] or air guns [Lorenz and Shandera 2000] has the potential to meet this objective. In this paper we present
the development of a tethered harpoon sampling and sample handling system operated from an aerial platform for
in-situ astrobiological investigations. The harpoon system can be driven into the sample using gravity, pyro, spring
or compressed gas mechanisms and is retrieved using a spooling mechanism. The system description and
preliminary test results are presented.

Several researchers are actively studying Ionomeric polymer transducers (IPT) as a large strain low voltage Electro-
Active Polymer (EAP) actuator. EAPs are devices that do not contain any moving parts leading to a potential large life
time. Furthermore, they are light weight and flexible. IPT have the ability to generate bending strains on the order 5%
when +2V potential is applied across its thickness. As sensors however, IPTs are proven to be superior compared to any
other EAP material when a charge amplifier is used as a signal conditioner. Furthermore, researchers has developed
miniature sensors from IPTs that could be flush mounted to a surface and measure shear stresses due to fluid flow at
even low Reynolds numbers. Sensor resolution is on the order of 10 mPa enables it to be useful as a wall shear stress
sensor for several aero/hydrodynamic and biomedical applications. In this paper a new signal conditioning circuit is
designed with superior sensing capabilities compared to the old circuit. In the new circuit the IPT is biased with a small
voltage on the order of 5mV to 25 mV. Initial experimental results demonstrated 30% enhancement in signal to noise
ratio compared to the old circuit. Furthermore, this circuit enables the use of IPT polymers with larger capacitance
compared to the previous circuits. Akle et al. demonstrated that the capacitance of an ionic polymer transducer is
proportional to transducer performance. Ionic polymers are generally made of an ion exchange membrane, typically
Nafion, coated with a flexible electrode. In this study the Direct Assembly Process (DAP) is used for the fabrication of
IPT. The DAP consists of mixing a metal particulate with an ionomer solution and spraying it directly on a diluent
saturated ion conducting membrane. The thickness of the electrode is controlled by altering the amount of the
ionomer/metal mix sprayed on the membrane. Thicker electrodes provide IPT with a larger capacitance, and hence larger
sensitivity is obtained using the new circuit. It was impossible to use the previous signal conditioning circuit for high
capacitance sensors. Finally an attempt to model these sensors along with the circuit is provided. By understanding the
interaction between the IPT and the signal conditioning circuit we can create devices with even higher sensitivity. The
presented circuit will help in modeling and predicting the response of the sensor.

Fatigue cracks initiating at fastener hole locations in metallic structure are among the most common form of
airframe damage. Current methods for inspecting airframes for these cracks are manual, whereby inspectors rely on nondestructive
inspection equipment or hand-held probes to scan over areas to be monitored. Use of this equipment often
demands disassembly of the airframe to search appropriate hole locations for cracks, which elevates the complexity and
cost of maintenance inspections.
In this study an Additive, Interleaved, Multi-layer Electromagnetic (AIME) sensor was developed and
integrated with the shank of a fastener to form a Structural Health Monitoring Fastener, a new technology targeted at insitu
detection of fastener hole cracks. The major advantages of the Structural Health Monitoring (SHM) Fastener over
other SHM technologies are its installation, which does not require joint layer disassembly, its capability to detect inner
layer cracks in a multi-layer joint, and its capability to operate in a continuous monitoring mode.
The AIME sensor design, SHM Fastener, and complete SHM system are presented along with experimental
results from a series of single-layer and bolted double lap-joint aluminum specimens to validate the capability of these
sensors to monitor metallic joints for fastener hole cracks and loads. Fatigue cracks were successfully tracked to over
0.7 inches from the fastener hole in these tests. Sensor output obtained from single-layer fatigue specimens was
compared with analytical predictions for fatigue crack growth versus cycle number showing a good correlation in trend
between sensor output and predicted crack size.

We present an SHM system integrating both the impedance and the Lamb wave propagation method on a single board,
while sharing the same DSP (Digital Signal Processing) processor and the piezoelectric patches. Three functional blocks,
such as signal excitation/generation, signal sensing, and data processing, were implemented to incorporate the Lamb
wave method into our existing impedance-based SHM system. Both pitch-and-catch and pulse-and-echo schemes were
implemented for damage detection and location, respectively. Through synergetic integration of the two methods, our
SHM system can detect various types of simulated damages on aluminum plates.

Structural health monitoring (SHM) is an emerging field in which smart materials interrogate structural components
to predict failure, expedite needed repairs, and thus increase the useful life of those components. Piezoelectric wafer
active sensors (PWAS) have been previously adhesively-bonded to structures and demonstrate the ability to detect and
locate cracking, corrosion, and disbonding through use of pitch-catch, pulse-echo, electro/mechanical impedance, and
phased array technology. The present research considers structurally-integrated PWAS that can be fabricated directly to
the structural substrate using thin-film nano technologies (e.g., pulsed-laser deposition, sputtering, chemical vapor
deposition, etc.) Because these novel PWAS are made up of nano layers they are dubbed nano-PWAS. Nano-PWAS
research consists of two parts, thin-film fabrication and nano-PWAS construction. The first part is how to fabricate the
piezoelectric thin-film on structure materials. In our research, ferroelectric BaTiO3 (BTO) thin films were successfully
deposited on structure material Ni and Ti by pulsed laser deposition under the optimal synthesis conditions.
Microstructural studies revealed that the as-grown BTO thin films have the nanopillar structures and the good interface
structures with no inter-diffusion or reaction. The dielectric and ferroelectric property measurements exhibit that the
BTO films have a relatively large dielectric constant, a small dielectric loss, and an extremely large piezoelectric
response with a symmetric hysteresis loop. The second part is nano-PWAS construction and how they are related to the
active SHM interrogation methods. Nano-PWAS architecture achieved through thin-film deposition technology and its
potential application for SHM were discussed here. The research objective is to develop the fabrication and optimum
design of thin-film nano-PWAS for structural health monitoring applications.